Displaying similar documents to “Adaptive algorithm for noisy autoregressive signals.”

Filtering of signals transmitted in multichannel from Chandrasekhar and Riccati recursions.

S. Nakamori, A. Hermoso, J. Jiménez, J. Linares (2005)

Extracta Mathematicae

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In this paper two recursive algorithms are proposed and compared as a solution of the least mean-squared error linear filtering problem of a wide-sense stationary scalar signal from uncertain observations perturbed by white and coloured additive noises. Considering that the state-space model of the signal is not available and that the variables modelling the uncertainty are not independent, the proposed algorithms are derived by using covariance information. The difference between both...

An efficient algorithm for estimating the parameters of superimposed exponential signals in multiplicative and additive noise

Jiawen Bian, Huiming Peng, Jing Xing, Zhihui Liu, Hongwei Li (2013)

International Journal of Applied Mathematics and Computer Science

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This paper considers parameter estimation of superimposed exponential signals in multiplicative and additive noise which are all independent and identically distributed. A modified Newton-Raphson algorithm is used to estimate the frequencies of the considered model, which is further used to estimate other linear parameters. It is proved that the modified Newton-Raphson algorithm is robust and the corresponding estimators of frequencies attain the same convergence rate with Least Squares...

Identifiability and estimation of pharmacokinetic parameters for the ligands of the macrophage mannose receptor

Nathalie Verdiere, Lilianne Denis-Vidal, Ghislaine Joly-Blanchard, Dominique Domurado (2005)

International Journal of Applied Mathematics and Computer Science

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The aim of this paper is numerical estimation of pharmacokinetic parameters of the ligands of the macrophage mannose receptor, without knowing it a priori the values of these parameters. However, it first requires a model identifiability analysis, which is done by applying an algorithm implemented in a symbolic computation language. It is shown that this step can lead to a direct numerical estimation algorithm. In this way, a first estimate is computed from noisy simulated observations...